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Pandas DataFrame: Add one row in an existing DataFrame


Write a Pandas program to add one row in an existing DataFrame.

Sample data:
Original DataFrame
col1 col2 col3
0 1 4 7
1 4 5 8
2 3 6 9
3 4 7 0
4 5 8 1
After add one row:
col1 col2 col3
0 1 4 7
1 4 5 8
2 3 6 9
3 4 7 0
4 5 8 1
5 10 11 12

Sample Solution :

Python Code :

import pandas as pd
import numpy as np
d = {'col1': [1, 4, 3, 4, 5], 'col2': [4, 5, 6, 7, 8], 'col3': [7, 8, 9, 0, 1]}
df = pd.DataFrame(data=d)
print("Original DataFrame")
print(df)
print('After add one row:')
df2 = {'col1': 10, 'col2': 11, 'col3': 12}
df = df.append(df2, ignore_index=True)
print(df)

Sample Output:

   Original DataFrame
   col1  col2  col3
0     1     4     7
1     4     5     8
2     3     6     9
3     4     7     0
4     5     8     1
After add one row:
   col1  col2  col3
0     1     4     7
1     4     5     8
2     3     6     9
3     4     7     0
4     5     8     1
5    10    11    12               

Explanation:

The code creates a Pandas DataFrame df from a Python dictionary ‘d’, which has three keys 'col1', 'col2', and 'col3', and corresponding values that are lists of integers. Then, a new Python dictionary df2 is created with the same keys, but with a single set of values.

df = df.append(df2, ignore_index=True): This code is used to add ‘df2’ as a new row to the DataFrame df. The ignore_index parameter is set to True to reset the index of the appended DataFrame.

Finally print() function prints the resulting DataFrame.

Python-Pandas Code Editor:

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